What is Mapreduce equivalent to top() function in Spark?
I am trying to find the equivalent solution to top() and take() functions in spark, for Mapreduce implementation. I want to extract the top k values, without saving the whole key, value pairs.
apache-spark mapreduce
edited Nov 21 '18 at 6:47
Ram Ghadiyaram
16.4k64477
asked Nov 21 '18 at 4:32
Sadaf TafazoliSadaf Tafazoli
1
add a comment |
I am trying to find the equivalent solution to top() and take() functions in spark, for Mapreduce implementation. I want to extract the top k values, without saving the whole key, value pairs.
apache-spark mapreduce
edited Nov 21 '18 at 6:47
Ram Ghadiyaram
16.4k64477
asked Nov 21 '18 at 4:32
Sadaf TafazoliSadaf Tafazoli
1
add a comment |
I am trying to find the equivalent solution to top() and take() functions in spark, for Mapreduce implementation. I want to extract the top k values, without saving the whole key, value pairs.
apache-spark mapreduce
edited Nov 21 '18 at 6:47
Ram Ghadiyaram
16.4k64477
asked Nov 21 '18 at 4:32
Sadaf TafazoliSadaf Tafazoli
1
I am trying to find the equivalent solution to top() and take() functions in spark, for Mapreduce implementation. I want to extract the top k values, without saving the whole key, value pairs.
apache-spark mapreduce
apache-spark mapreduce
edited Nov 21 '18 at 6:47
Ram Ghadiyaram
16.4k64477
asked Nov 21 '18 at 4:32
Sadaf TafazoliSadaf Tafazoli
1
edited Nov 21 '18 at 6:47
Ram Ghadiyaram
16.4k64477
asked Nov 21 '18 at 4:32
Sadaf TafazoliSadaf Tafazoli
1
edited Nov 21 '18 at 6:47
Ram Ghadiyaram
16.4k64477
edited Nov 21 '18 at 6:47
Ram Ghadiyaram
16.4k64477
edited Nov 21 '18 at 6:47
Ram Ghadiyaram
16.4k64477
16.4k64477
asked Nov 21 '18 at 4:32
Sadaf TafazoliSadaf Tafazoli
1
asked Nov 21 '18 at 4:32
Sadaf TafazoliSadaf Tafazoli
1
asked Nov 21 '18 at 4:32
Sadaf TafazoliSadaf Tafazoli
1
1
add a comment |
add a comment |
1 Answer
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There is not a direct equivalent. If you need to do something similar without having Spark, I generally use Pig
It requires at least two map reduce phases. One to process the data, then another to collect the data you actually want
In the mapper, you set null writable (or some, single valued key), then emit all values, forcing them to a single reducer.
In the reducer, you collect all values you want to sort or emit into a limited size collection. I recommend a TreeMap or Binary Heap, because they auto-sort. Then, you loop over the size of that collection for K values
answered Nov 21 '18 at 4:36
cricket_007cricket_007
80.8k1142110
add a comment |
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1 Answer
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active
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1 Answer
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active
oldest
votes
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oldest
votes
active
oldest
votes
There is not a direct equivalent. If you need to do something similar without having Spark, I generally use Pig
It requires at least two map reduce phases. One to process the data, then another to collect the data you actually want
In the mapper, you set null writable (or some, single valued key), then emit all values, forcing them to a single reducer.
In the reducer, you collect all values you want to sort or emit into a limited size collection. I recommend a TreeMap or Binary Heap, because they auto-sort. Then, you loop over the size of that collection for K values
answered Nov 21 '18 at 4:36
cricket_007cricket_007
80.8k1142110
add a comment |
There is not a direct equivalent. If you need to do something similar without having Spark, I generally use Pig
It requires at least two map reduce phases. One to process the data, then another to collect the data you actually want
In the mapper, you set null writable (or some, single valued key), then emit all values, forcing them to a single reducer.
In the reducer, you collect all values you want to sort or emit into a limited size collection. I recommend a TreeMap or Binary Heap, because they auto-sort. Then, you loop over the size of that collection for K values
answered Nov 21 '18 at 4:36
cricket_007cricket_007
80.8k1142110
add a comment |
There is not a direct equivalent. If you need to do something similar without having Spark, I generally use Pig
It requires at least two map reduce phases. One to process the data, then another to collect the data you actually want
In the mapper, you set null writable (or some, single valued key), then emit all values, forcing them to a single reducer.
In the reducer, you collect all values you want to sort or emit into a limited size collection. I recommend a TreeMap or Binary Heap, because they auto-sort. Then, you loop over the size of that collection for K values
answered Nov 21 '18 at 4:36
cricket_007cricket_007
80.8k1142110
There is not a direct equivalent. If you need to do something similar without having Spark, I generally use Pig
It requires at least two map reduce phases. One to process the data, then another to collect the data you actually want
In the mapper, you set null writable (or some, single valued key), then emit all values, forcing them to a single reducer.
In the reducer, you collect all values you want to sort or emit into a limited size collection. I recommend a TreeMap or Binary Heap, because they auto-sort. Then, you loop over the size of that collection for K values
answered Nov 21 '18 at 4:36
cricket_007cricket_007
80.8k1142110
answered Nov 21 '18 at 4:36
cricket_007cricket_007
80.8k1142110
answered Nov 21 '18 at 4:36
cricket_007cricket_007
80.8k1142110
answered Nov 21 '18 at 4:36
cricket_007cricket_007
80.8k1142110
80.8k1142110
add a comment |
add a comment |
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